Optimization of Optical Machine Structure by Backpropagation Neural Network Based on Particle Swarm Optimization and Bayesian Regularization Algorithms

Fit of the highly nonlinear functional relationship between input variables and output response is important and challenging for the optical machine structure optimization design process. The backpropagation neural network method based on particle swarm optimization and Bayesian regularization algor...

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Vydáno v:Materials Ročník 14; číslo 11; s. 2998
Hlavní autoři: Zhang, Xinyong, Sun, Liwei
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.06.2021
MDPI
Témata:
Accuracy
Algorithms
Back propagation
Back propagation networks
Bayesian analysis
Cameras
Design optimization
Efficiency
Finite element analysis
Model accuracy
Neural networks
Optimization
Particle swarm optimization
Prediction models
Predictions
Random variables
Regularization
Velocity
ISSN:1996-1944, 1996-1944
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Shrnutí:Fit of the highly nonlinear functional relationship between input variables and output response is important and challenging for the optical machine structure optimization design process. The backpropagation neural network method based on particle swarm optimization and Bayesian regularization algorithms (called BMPB) is proposed to solve this problem. A prediction model of the mass and first-order modal frequency of the supporting structure is developed using the supporting structure as an example. The first-order modal frequency is used as the constraint condition to optimize the lightweight design of the supporting structure’s mass. Results show that the prediction model has more than 99% accuracy in predicting the mass and the first-order modal frequency of the supporting structure, and converges quickly in the supporting structure’s mass-optimization process. The supporting structure results demonstrate the advantages of the method proposed in the article in terms of high accuracy and efficiency. The study in this paper provides an effective method for the optimized design of optical machine structures.
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ISSN:1996-1944
1996-1944
DOI:10.3390/ma14112998